BACKGROUND： It has proved that dynamic electroencephalogram （EEG） is definite in judging the outcome of ischemic hypoxic comatose patients, EEG is more sensitive to the cortical affection, but not sensitive to the ...BACKGROUND： It has proved that dynamic electroencephalogram （EEG） is definite in judging the outcome of ischemic hypoxic comatose patients, EEG is more sensitive to the cortical affection, but not sensitive to the subcortical and brainstem affections, thus it is necessary to clarify the indications of this technique in the clinical application.OBJECTIVE： To observe and compare the prognostic value of dynamic EEG and Glasgow coma score in comatose patients with different diseased region.DESIGN： A clinical case-controlled observation.SETTING： Union Hospital of Fujian Medical University.PARTICIPANTS： Sixty-eight comatose patients were selected from the Union Hospital affiliated to Fujian Medical University from June 1998 to January 2005. The diseased regions were identified using cranial CT （n =43） or MR （n =25）. According to different primarily diseased regions, the comatose patients were divided into two groups： ① brainstem affection group （n =23）： 13 males and 10 females, 14 - 62 years of age; ②diffuse cortical affection group （n =45）： 28 males and 17 females, 23 - 75 years of age.METHODS： The dynamic EEG and Glasgow coma score were examined in the 45 comatose patients with primarily cortical affection and 22 comatose patients with primarily brainstem affection at acute phase. The patients were followed-up for 3 months to observe the outcome, The termination of outcome judgment was 3 months after attack or the death. The clinical outcome was classified as complete rehabilitation, survived with disability, death or vegetative state. Correlations of dynamic EEG and Glasgow coma score with the outcome of patients were analyzed. The correlations of dynamic EEG grades and Glasgow coma scores with the outcome were analyzed, and the prognostic value of dynamic EEG grades was compared between the two groups.MAIN OUTCOME MEASURES： ① Correlations of dynamic EEG and Glasgow coma score with the outcome of patients; ② Comparison of the prognostic value of dynamic EEG grades between the two groups.RESULTS： All the 68 patients were involved in the analysis of results. ① Correlations of dynamic EEG grades and Glasgow scores and their correlation analysis： EEG grades had significant negative correlation with Glasgow coma scores in both the cortical affection group and brainstem affection group （r = - 0.743,- 0.564, P 〈 0.01, 0.05）. In the cortical affection group, the Glasgow coma scores and dynamic EEG grades in the patients with the outcome of death or vegetative state were significantly different from those with the outcome of rehabilitation （P 〈 0.05 - 0.01）. In the brainstem affection group, the Glasgow coma scores were only significantly different between the patients with outcome of rehabilitation and death （P 〈 0.05）, and there was no significant difference in dynamic EEG grades among the three prognostic states （P 〉 0.05）. ②Comparison of the prognostic value of dynamic EEG grades between comatose patients with cortical affection and brainstem affection： The sensitivity, specificity and accuracy were all higher （P 〈 0.05）, while the error rate was lower （P〈0.05） in the cortical affection group than in the brainstem affection group.CONCLUSION： Dynamic EEG was valuable in predicting the outcome of comatose patients with primarily cortical affection, but it was not certainly valuable in those with primarily brainstem affection.展开更多
Electroencephalogram signals are time-varying complex electrophysiological signals. Existing studies show that approximate entropy, which is a nonlinear dynamics index, is not an ideal method for electroencephalogram ...Electroencephalogram signals are time-varying complex electrophysiological signals. Existing studies show that approximate entropy, which is a nonlinear dynamics index, is not an ideal method for electroencephalogram analysis. Clinical electroencephalogram measurements usually contain electrical interference signals, creating additional challenges in terms of maintaining robustness of the analytic methods. There is an urgent need for a novel method of nonlinear dynamical analysis of the electroencephalogram that can characterize seizure-related changes in cerebral dynamics. The aim of this paper was to study the fluctuations of approximate entropy in preictal, ictal, and postictal electroencephalogram signals from a patient with absence seizures, and to improve the algorithm used to calculate the approximate entropy. The approximate entropy algorithm, especially our modified version, could accurately describe the dynamical changes of the brain during absence seizures. We could also demonstrate that the complexity of the brain was greater in the normal state than in the ictal state. The fluctuations of the approximate entropy before epileptic seizures observed in this study can form a good basis for further study on the prediction of seizures with nonlinear dynamics.展开更多
In present work,EEG and BP were used as the indexes to observe the relationbetween the change of EEG and the change of BP in the endotoxic shocked rats。At maintainingshock for 1 hr,dysrhythmia of EEG appeared in 38/4...In present work,EEG and BP were used as the indexes to observe the relationbetween the change of EEG and the change of BP in the endotoxic shocked rats。At maintainingshock for 1 hr,dysrhythmia of EEG appeared in 38/46 cases.Simultaneously,there was a markeddrop in Bp,P【0.05.Following the shocked time prolonged,dysrhythmia was getting severe。AfterEA”Rengzhong"(n=14)or“Zusanli”(n=12),BP was significantly increased(P【0.05),anddysrhythmia of EEG showed clear improvement in most of the rats。There was a close relation be-tween the changes of EEG and BP,the change of EEG had a direct bearing on the change of BP.展开更多
This work presents a novel least squares matrix algorithm (LSM) for the analysis of rapidly changing systems using state-space modelling. The LSM algorithm is based on the Hankel structured data matrix representation....This work presents a novel least squares matrix algorithm (LSM) for the analysis of rapidly changing systems using state-space modelling. The LSM algorithm is based on the Hankel structured data matrix representation. The state transition matrix is updated without the use of any forgetting function. This yields a robust estimation of model parameters in the presence of noise. The computational complexity of the LSM algorithm is comparable to the speed of the conventional recursive least squares (RLS) algorithm. The knowledge of the state transition matrix enables feasible numerical operators such as interpolation, fractional differentiation and integration. The usefulness of the LSM algorithm was proved in the analysis of the neuroelectric signal waveforms.展开更多
基金the NaturalScience Foundation of Fujian Province, No. C0310021
文摘BACKGROUND： It has proved that dynamic electroencephalogram （EEG） is definite in judging the outcome of ischemic hypoxic comatose patients, EEG is more sensitive to the cortical affection, but not sensitive to the subcortical and brainstem affections, thus it is necessary to clarify the indications of this technique in the clinical application.OBJECTIVE： To observe and compare the prognostic value of dynamic EEG and Glasgow coma score in comatose patients with different diseased region.DESIGN： A clinical case-controlled observation.SETTING： Union Hospital of Fujian Medical University.PARTICIPANTS： Sixty-eight comatose patients were selected from the Union Hospital affiliated to Fujian Medical University from June 1998 to January 2005. The diseased regions were identified using cranial CT （n =43） or MR （n =25）. According to different primarily diseased regions, the comatose patients were divided into two groups： ① brainstem affection group （n =23）： 13 males and 10 females, 14 - 62 years of age; ②diffuse cortical affection group （n =45）： 28 males and 17 females, 23 - 75 years of age.METHODS： The dynamic EEG and Glasgow coma score were examined in the 45 comatose patients with primarily cortical affection and 22 comatose patients with primarily brainstem affection at acute phase. The patients were followed-up for 3 months to observe the outcome, The termination of outcome judgment was 3 months after attack or the death. The clinical outcome was classified as complete rehabilitation, survived with disability, death or vegetative state. Correlations of dynamic EEG and Glasgow coma score with the outcome of patients were analyzed. The correlations of dynamic EEG grades and Glasgow coma scores with the outcome were analyzed, and the prognostic value of dynamic EEG grades was compared between the two groups.MAIN OUTCOME MEASURES： ① Correlations of dynamic EEG and Glasgow coma score with the outcome of patients; ② Comparison of the prognostic value of dynamic EEG grades between the two groups.RESULTS： All the 68 patients were involved in the analysis of results. ① Correlations of dynamic EEG grades and Glasgow scores and their correlation analysis： EEG grades had significant negative correlation with Glasgow coma scores in both the cortical affection group and brainstem affection group （r = - 0.743,- 0.564, P 〈 0.01, 0.05）. In the cortical affection group, the Glasgow coma scores and dynamic EEG grades in the patients with the outcome of death or vegetative state were significantly different from those with the outcome of rehabilitation （P 〈 0.05 - 0.01）. In the brainstem affection group, the Glasgow coma scores were only significantly different between the patients with outcome of rehabilitation and death （P 〈 0.05）, and there was no significant difference in dynamic EEG grades among the three prognostic states （P 〉 0.05）. ②Comparison of the prognostic value of dynamic EEG grades between comatose patients with cortical affection and brainstem affection： The sensitivity, specificity and accuracy were all higher （P 〈 0.05）, while the error rate was lower （P〈0.05） in the cortical affection group than in the brainstem affection group.CONCLUSION： Dynamic EEG was valuable in predicting the outcome of comatose patients with primarily cortical affection, but it was not certainly valuable in those with primarily brainstem affection.
基金supported by the National Natural Science Foundation of China, No.10671213 and 11101440the Natural Science Foundation of Guangdong ProvinceFundamental Research Funds for the Central Universities
文摘Electroencephalogram signals are time-varying complex electrophysiological signals. Existing studies show that approximate entropy, which is a nonlinear dynamics index, is not an ideal method for electroencephalogram analysis. Clinical electroencephalogram measurements usually contain electrical interference signals, creating additional challenges in terms of maintaining robustness of the analytic methods. There is an urgent need for a novel method of nonlinear dynamical analysis of the electroencephalogram that can characterize seizure-related changes in cerebral dynamics. The aim of this paper was to study the fluctuations of approximate entropy in preictal, ictal, and postictal electroencephalogram signals from a patient with absence seizures, and to improve the algorithm used to calculate the approximate entropy. The approximate entropy algorithm, especially our modified version, could accurately describe the dynamical changes of the brain during absence seizures. We could also demonstrate that the complexity of the brain was greater in the normal state than in the ictal state. The fluctuations of the approximate entropy before epileptic seizures observed in this study can form a good basis for further study on the prediction of seizures with nonlinear dynamics.
基金The Project Supported by National Natural Science Foundation of China
文摘In present work,EEG and BP were used as the indexes to observe the relationbetween the change of EEG and the change of BP in the endotoxic shocked rats。At maintainingshock for 1 hr,dysrhythmia of EEG appeared in 38/46 cases.Simultaneously,there was a markeddrop in Bp,P【0.05.Following the shocked time prolonged,dysrhythmia was getting severe。AfterEA”Rengzhong"(n=14)or“Zusanli”(n=12),BP was significantly increased(P【0.05),anddysrhythmia of EEG showed clear improvement in most of the rats。There was a close relation be-tween the changes of EEG and BP,the change of EEG had a direct bearing on the change of BP.
文摘This work presents a novel least squares matrix algorithm (LSM) for the analysis of rapidly changing systems using state-space modelling. The LSM algorithm is based on the Hankel structured data matrix representation. The state transition matrix is updated without the use of any forgetting function. This yields a robust estimation of model parameters in the presence of noise. The computational complexity of the LSM algorithm is comparable to the speed of the conventional recursive least squares (RLS) algorithm. The knowledge of the state transition matrix enables feasible numerical operators such as interpolation, fractional differentiation and integration. The usefulness of the LSM algorithm was proved in the analysis of the neuroelectric signal waveforms.
